Fetching the paper…
Reading the bibliography…
The debate on AI ethics largely focuses on technical improvements and stronger regulation to prevent accidents or misuse of AI, with solutions relying on holding individual actors accountable for responsible AI development.
The 2008 Food Price Crisis: Rethinking Food Security Policies
A. Mittal · 2009
Earlier work this paper cites.
Short-termism and the threat from climate change
H. M. Paulson Jr · 2015
Earlier work this paper cites.
There is a Blind Spot in AI Research
K. Crawford and R. Calo · 2016
Earlier work this paper cites.
Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates
C. Zhao et al · 2017
Earlier work this paper cites.
’About Indigo Ag’, 2018
Indigo Ag · 2018
Earlier work this paper cites.
The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
M. Brundage et al · 2018
Earlier work this paper cites.
An AI Race for Strategic Advantage: Rhetoric and Risks
S. Cave and S. S. ÓhÉigeartaigh · 2018
Earlier work this paper cites.
AI Governance: A Research Agenda
A. Dafoe · 2018
Earlier work this paper cites.
’Environmental Risk Reporting & Impact Monitoring for Government and Public Sector Organisations’, 2018
Ecometrica · 2018
Earlier work this paper cites.
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
J. Hwang, P. Orenstein, J. Cohen, K. Pfeiffer, and L. Mackey · 2018
Earlier work this paper cites.
The Inequality of Climate Change From 1.5 to 2 C of Global Warming
A. D. King and L. J. Harrington · 2018
Earlier work this paper cites.
Earth Science Deep Learning: Applications and Lessons Learned
M. Maskey, R. Ramachandran, J.J. Miller, J. Zhang, and I. Gurung · 2018
Cited alongside, same era.
Should all medical research be published? The moral responsibility of medical journal editors
T. Ploug · 2018
Cited alongside, same era.
Deep Learning to Represent Subgrid Processes in Climate Models
S. Rasp, M. S. Pritchard, and P. Gentine · 2018
Cited alongside, same era.
Future Warming Increases Probability of Globally Synchronized Maize Production Shocks
M. Tigchelaar, D. S. Battisti, R. L. Naylor, and D. K. Ray · 2018
Cited alongside, same era.
AI Now Report 2018
M. Whittaker et al · 2018
Cited alongside, same era.
’Building climate resilience’, 2019
Acclimatise · 2019
Cited alongside, same era.
Global Warming Has Increased Global Economic Inequality
N. S. Diffenbaugh and M. Burke · 2019
Closest in time.
Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning
D. Greene, A. L. Hoffmann, and L. Stark · 2019
Closest in time.
’Secretary-General’s message for Third Artificial Intelligence for Good Summit’, May 2019
A. Gutteres · 2019
Closest in time.
The Ethics of AI Ethics – An Evaluation of Guidelines
T. Hagendorff · 2019
Closest in time.
’Jupiter Services: Dynamic Technology Delivers Precise Asset-Level Predictions’, 2019
Jupiter Intelligence · 2019
Closest in time.
Artificial Intelligence: the Global Landscape of Ethics Guidelines
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse gas fluxes in Terrestrial Ecosystems Summary for Policymakers
A. Arneth et al · 2019
Cited alongside, same era.
The Role of Cooperation in Responsible AI Development
A. Askell, M. Brundage, and G. Hadfield · 2019
Cited alongside, same era.
’Weather Intelligence For A Changing Climate’, 2019
aWhere · 2019
Cited alongside, same era.
Standards for AI Governance: International Standards to Enable Global Coordination in AI Research & Development
P. Cihon · 2019
Cited alongside, same era.
’Will the climate services industry only help those who can pay?’, August 2019
G. Dembicki · 2019
Cited alongside, same era.
Osaka, 2019a. G20
’G20 AI Principles’
Cited in the paper.
A. Jobin, M. Ienca, and E. Vayena · 2019
Closest in time.
AI Ethics – Too Principled to Fail?
Brent Mittelstadt · 2019
Closest in time.
Tackling Climate Change with Machine Learning
D. Rolnick et al · 2019
Closest in time.
Regulator looking at use of facial recognition at King’s Cross site
Dan Sabbagh · 2019
Closest in time.
State of Food Security and Nutrition in the World 2019: Safeguarding Against Economic Slowdowns and Downturns
M. Torrero Cullen et al · 2019
Closest in time.
Thinking About Risks From AI: Accidents, Misuse and Structure, February 2019
R. Zwetsloot and A. Dafoe · 2019
Closest in time.